Results 1 to 10 of about 233 (124)

FLAME-VQA: A Fuzzy Logic-Based Model for High Frame Rate Video Quality Assessment

open access: yesFuture Internet, 2023
In the quest to optimize user experience, network, and service, providers continually seek to deliver high-quality content tailored to individual preferences. However, predicting user perception of quality remains a challenging task, given the subjective
Å tefica Mrvelj, Marko Matulin
doaj   +4 more sources

UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content [PDF]

open access: yesIEEE Transactions on Image Processing, 2021
IEEE Transactions on Image Processing ...
Zhengzhong Tu   +2 more
exaly   +4 more sources

SB-VQA: A Stack-Based Video Quality Assessment Framework for Video Enhancement

open access: yes2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023
In recent years, several video quality assessment (VQA) methods have been developed, achieving high performance. However, these methods were not specifically trained for enhanced videos, which limits their ability to predict video quality accurately based on human subjective perception.
Ding-Jiun Huang   +5 more
exaly   +3 more sources

Blind Video Quality Assessment for Ultra-High-Definition Video Based on Super-Resolution and Deep Reinforcement Learning [PDF]

open access: yesSensors, 2023
Ultra-high-definition (UHD) video has brought new challenges to objective video quality assessment (VQA) due to its high resolution and high frame rate.
Zefeng Ying, Da Pan, Ping Shi
doaj   +2 more sources

Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment

open access: yes2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023
Accepted by CVPR 2023 ...
Kun Yuan, Xing Wen
exaly   +3 more sources

No-Reference Video Quality Assessment Using the Temporal Statistics of Global and Local Image Features [PDF]

open access: yesSensors, 2022
During acquisition, storage, and transmission, the quality of digital videos degrades significantly. Low-quality videos lead to the failure of many computer vision applications, such as object tracking or detection, intelligent surveillance, etc.
Domonkos Varga
doaj   +2 more sources

Video quality prediction and classification using XGBoost under variable encoding and network conditions [PDF]

open access: yesScientific Reports
This study presents a machine learning-based framework for video quality assessment (VQA). This framework enables the mapping of objective metric outputs, such as Structural Similarity Index Measure (SSIM) and Video Multimethod Assessment Fusion (VMAF ...
Jaroslav Frnda   +4 more
doaj   +2 more sources

FAST-VQA: Efficient End-to-End Video Quality Assessment with Fragment Sampling

open access: yesLecture Notes in Computer Science, 2022
Current deep video quality assessment (VQA) methods are usually with high computational costs when evaluating high-resolution videos. This cost hinders them from learning better video-quality-related representations via end-to-end training. Existing approaches typically consider naive sampling to reduce the computational cost, such as resizing and ...
Haoning Wu   +2 more
exaly   +3 more sources

Towards Quality Assessment for Arbitrary Translational 6DoF Video: Subjective Quality Database and Objective Assessment Metric [PDF]

open access: yesEntropy
Arbitrary translational Six Degrees of Freedom (6DoF) video represents a transitional stage towards immersive terminal videos, allowing users to freely switch viewpoints for a 3D scene experience. However, the increased freedom of movement introduces new
Chongchong Jin, Yeyao Chen
doaj   +2 more sources

A Perspective on Quality Evaluation for AI-Generated Videos [PDF]

open access: yesSensors
Recent breakthroughs in AI-generated content (AIGC) have transformed video creation, empowering systems to translate text, images, or audio into visually compelling stories.
Zhichao Zhang, Wei Sun, Guangtao Zhai
doaj   +2 more sources

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